Reduced-order, computational fluid dynamics-informed pressure-flow simulation of endoscopic injection therapy in pediatric vesicoureteral reflux: An in-silico evaluation of technique-dependent outcomes.

INTRODUCTION

Endoscopic bulking therapy is widely used to treat vesicoureteral reflux (VUR), yet technique selection remains largely empiric and outcomes vary by reflux grade and bladder dynamics. We developed a hypothesis-generating, reduced-order, computational fluid dynamics (CFD)-informed pressure-flow simulation intended to explore hydrodynamic mechanisms and injection-strategy tradeoffs.

METHODS

The model represents the bladder, ureterovesical junction, ureter, and renal pelvis as coupled pressure-flow elements. VUR grade templates modify competence, reverse resistance, dilation, tortuosity, compliance, and peristalsis; bladder-bowel dysfunction (BBD) is represented only as stylized pressure/outlet phenotypes. Injection modifies reverse and antegrade resistance through technique- and volume-dependent transformations. Reflux fraction (RF) was reflux volume divided by reflux plus antegrade volume; the obstruction index (OI) was a modeling safety ceiling, not a clinically validated threshold.

RESULTS

In the balanced 75-stratum simulation, the base-case OI ceiling selected Double HIT in 65 strata, Double HIT + STING in 9 strata, and HIT in 1 stratum. These are model outputs reflecting encoded multi-site geometry and volume-splitting assumptions. In the grade-V reference sweep, STING did not reach modeled RF resolution and exceeded the OI ceiling across tested volumes. Bilateral simulations showed small contralateral effects under the current shared-bladder coupling assumptions rather than strong clinical coupling. OI-threshold, mound-sigmoid, and tornado sensitivity analyses were added or specified to evaluate robustness of the model outputs.

CONCLUSIONS

This CFD-informed model offers a transparent, hypothesis-generating framework for comparing hydrodynamic consequences of endoscopic injection strategies. It does not establish clinical superiority, predict individual outcomes, or define validated treatment thresholds; external validation is required before clinical decision use.